Hierarchical control of soft manipulators towards unstructured interactions

Hierarchical Basis for Unstructured

Towards Tree-structure based Hierarchical Hybrid Soft Computing

s: There are three basic multilevel structures for hierarchical models, namely, incremental, aggregated and cascaded. Designing of these hierarchical models faces many difficulties including determination of the hierarchical structure, parameter identification and input variables selection for each submodels. A tree-structure based Hierarchical Hybrid Soft Computing (HHSC) framework is presente...

Adaptive RBF network control for robot manipulators

TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed netw...

Optimal discrete-time control of robot manipulators in repetitive tasks

Optimal discrete-time control of linear systems has been presented already. There are some difficulties to design an optimal discrete-time control of robot manipulator since the robot manipulator is highly nonlinear and uncertain. This paper presents a novel robust optimal discrete-time control of electrically driven robot manipulators for performing repetitive tasks. The robot performs repetit...

Discrete-time repetitive optimal control: Robotic manipulators

This paper proposes a discrete-time repetitive optimal control of electrically driven robotic manipulators using an uncertainty estimator. The proposed control method can be used for performing repetitive motion, which covers many industrial applications of robotic manipulators. This kind of control law is in the class of torque-based control in which the joint torques are generated by permanen...